Abstract Early detection of ongoing hemorrhage (OH) before onset of shock is a universally acknowledged great unmet need, and particularly important after trauma. Delays in the detection of OH are associated with a ?failure to rescue? and a dramatic deterioration in prognosis once the onset of clinically frank shock has occurred. While uniplex noninvasive technologies have failed to detect or diagnose complex disease states, we have demonstrated the superiority of multiplex approaches in silico. The goal of this STTR project is to develop a commercially viable optoimpedance sensor-based system that combines state-of-the-art noninvasive sensing technologies and advanced multivariable statistical algorithms. Phase I will involve three Aims: 1) D?esign, Fabricate and Test Opto-Impedance oPiic sensors, 2) Develop of Mobile App, Data and ML Pipeline on Secure Cloud, and 3) Evaluate oPiics on an Unanesthetized Upright Porcine Hemorrhage Model. By derisking the hardware challenges, we will be well-positioned for a Phase II application to optimize oPiic design and manufacturing, fold-in predictive algorithms under current development with DOD support, and validate with a clinical trial in critical care setting.